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Feature detection using oriented local energy for 3D confocal microscope images 3rd

3rd International computer science Conference, ICSC 1995

作者： Pudney, Chris Kovesi, Peter Robbins, Ben Biomedical Confocal Microscopy Research Centre Department of Pharmacology The University of Western Australia NedlandsWA6907 Australia Robotics and Vision Research Group Department of Computer Science The University of Western Australia NedlandsWA6907 Australia

ISBN: (纸本)9783540606970

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature types: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters that are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency-space and multiplied by the image's Fourier transform. Results are presented for real confocal images and a synthetic 3D image volume. These results are compared with those from a 3D implementation of the Sobel edge detecto. © Springer-Verlag Berlin Heidelberg 1995.

关键词： Feature extraction

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A 3D local energy surface detector for confocal microscope images

A 3D local energy surface detector for confocal microscope i...

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Australian and New Zealand Conference on intelligent Information Systems

作者： C. Pudney P. Kovesi B. Robbins Biomedical Confocal Microscopy Research Centre Department of Pharmacology University of Western Australia Nedlands WA Australia Robotics and Vision Research Group Department of Computer Science University of Western Australia Nedlands WA Australia

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by M.C. Morrone and R.A. Omens (1987) marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature profiles: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters. The filters are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency space and multiplied by the image's Fourier transform. Results are presented for real confocal images and synthetic 3D image volumes.

关键词： Detectors Microscopy computer vision Filters Data analysis Image analysis Image edge detection Convolution Frequency Fourier transforms

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Face recognition: The problem of compensating for changes in illumination direction 3rd

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3rd European Conference on computer vision, ECCV 1994

作者： Moses, Yael Adini, Yael Ullman, Shimon Department of Applied Mathematics and Computer Science The Weizmann Institute of Science Rehovot76100 Israel Robotics Group Dept Engineering Science Oxford University Parks Rd OX1 3PJ United Kingdom

ISBN: (纸本)9783540579564

Recognizing faces is a difficult problem due to the generally similar shape of faces combined with the considerable variability in images of the same face under different viewing conditions. In this paper we consider image variation due mainly to illumination conditions. We study several image representations that are often considered insensitive to changes of illumination conditions, such as edge maps, derivatives of the grey-level image, and the image convolved with Gabor filters. For each of these representations, we compare the differences between images of the same face under different imaging conditions, with differences between images of distinct faces. The comparison is performed using a controlled database of faces, in which each of the imaging parameters (illumination, viewing position, and expression) is controlled separately. The main result of these studies is that the variations between the images of the same face due to illumination and viewing directions are almost always larger than image variations due to a change in face identity. For illumination changes, this reversal is ahnost complete except for representations that emphasized the horizontal features. However, even for these representations, systems based only on comparing such representations will fail to recognize up to 30% of the faces in our database. We conclude that these representations are insufficient by themselves to overcome the variation between images due to changes in illumination direction as well as changes due to viewing position and expression. © Springer-Verlag Berlin Heidelberg 1994.

关键词： Gabor filters

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Industrial machine vision: lessons and challenges

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Optics News 1987年第2期13卷 12-17页

作者： Steven W. Holland Robert B. Tilove STEVEN W. HOLLAND is an assistant department head in the Computer Science Dept. of General Motors Research Laboratories (GMR). He is responsible for research projects involving computer vision robotics mobile robotics process planning knowledge systems natural language advanced programming environments parallel processing and statistics. ROBERT B. TILOVE is senior staff research scientist and project leader of the machine perception project at GMR. His research interests include geometric modeling model-based programming and control of intelligent automation systems.

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关键词： Integral imaging Machine vision Measurement and metrology Optical systems Sensors Statistics

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Scientific and Technological Challenges in RoboCup

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Control, robotics, and Autonomous Systems 1000年第1期3卷 441-471页

作者： Minoru Asada Oskar von Stryk 1Symbiotic Intelligent Systems Research Center Institute for Open and Transdisciplinary Research Initiatives Osaka University Suita Osaka 565-0871 Japan email: asada@otri.osaka-u.ac.jp 2Simulation Systems Optimization and Robotics Group Department of Computer Science Technische Universität Darmstadt D-64289 Darmstadt Germany

Since its inception in 1997, RoboCup has developed into a truly unique and long-standing research community advancing robotics and artificial intelligence through various challenges, benchmarks, and test fields. The main purposes of this article are to evaluate the research and development achievements so far and to identify new challenges and related new research issues. Unlike other robot competitions and research conferences, RoboCup eliminates the boundaries between pure research activities and the development of full system designs with hardware and software implementations at a site open to the public. It also creates specific scientific and technological research and development challenges to be addressed. In this article, we provide an overview of RoboCup, including its league structure and related research issues. We also review recent studies across several research categories to show how participants (called RoboCuppers) address the research and development challenges before, during, and after the annual competitions. Among the diversity of research issues, we highlight two unique aspects of the challenges: the platform design of the robots and the game evaluations. Both of these aspects contribute to solving the research and development challenges of RoboCup and verifying the results from a common perspective (i.e., a more objective view). Finally, we provide concluding remarks and discuss future research directions.

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Similarity-Based Clustering 1

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丛书名： Lecture Notes in computer science

1000年

作者： Michael Biehl Barbara Hammer Michel Verleysen Thomas Villmann

ISBN: (数字)9783642018053

ISBN: (纸本)9783642018046

Similarity-based learning methods have a great potential as an intuitive and ?exible toolbox for mining, visualization,and inspection of largedata sets. They combine simple and human-understandable principles, such as distance-based classi?cation, prototypes, or Hebbian learning, with a large variety of di?erent, problem-adapted design choices, such as a data-optimum topology, similarity measure, or learning mode. In medicine, biology, and medical bioinformatics, more and more data arise from clinical measurements such as EEG or fMRI studies for monitoring brain activity, mass spectrometry data for the detection of proteins, peptides and composites, or microarray pro?les for the analysis of gene expressions. Typically, data are high-dimensional, noisy, and very hard to inspect using classic (e. g. , symbolic or linear) methods. At the same time, new technologies ranging from the possibility of a very high resolution of spectra to high-throughput screening for microarray data are rapidly developing and carry thepromiseofane?cient,cheap,andautomaticgatheringoftonsofhigh-quality data with large information potential. Thus, there is a need for appropriate - chine learning methods which help to automatically extract and interpret the relevant parts of this information and which, eventually, help to enable und- standingofbiologicalsystems,reliablediagnosisoffaults,andtherapyofdiseases such as cancer based on this information. Moreover, these application scenarios pose fundamental and qualitatively new challenges to the learning systems - cause of the speci?cs of the data and learning tasks. Since these characteristics are particularly pronounced within the medical domain, but not limited to it and of principled interest, this research topic opens the way towardimportant new directions of algorithmic design and accompanying theory.

关键词： Life sciences, general Computational Biology/Bioinformatics Biomedicine general Data Mining and Knowledge Discovery Information Storage and Retrieval computer Imaging, vision, Pattern Recognition and Graphics

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Recent Trends in Applied Artificial Intelligence 1

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丛书名： Lecture Notes in computer science

1000年

作者： Moonis Ali Tibor Bosse Jan Treur Koen V. Hindriks Catholijn M. Jonker Mark Hoogendoorn

ISBN: (数字)9783642385773

ISBN: (纸本)9783642385766

This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.

关键词： Artificial Intelligence Information Systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery computer Imaging, vision, Pattern Recognition and Graphics computer science, general

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Social robotics 1

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丛书名： Lecture Notes in computer science

1000年

作者： Bilge Mutlu Christoph Bartneck Jaap Ham Vanessa Evers Takayuki Kanda

ISBN: (数字)9783642255045

ISBN: (纸本)9783642255038

This book constitutes the refereed proceedings of the Third International Conference on Social robotics, ICSR 2011, held in Amsterdam, The Netherlands, in November 2011. The 23 revised full papers were carefully selected during two rounds of reviewing and improvement from 51 submissions. The papers are organized in topical sections on social interaction with robots; nonverbal interaction with social robots; robots in society; social robots in education; affective interaction with social robots; robots in the home.

关键词： Artificial Intelligence User Interfaces and Human computer Interaction computers and Society computer Appl. in Social and Behavioral sciences computer Imaging, vision, Pattern Recognition and Graphics Special Purpose and Application-Based Systems

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Applications of Evolutionary Computation 1

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丛书名： Lecture Notes in computer science

1000年

作者： Cecilia Chio Alexandros Agapitos Stefano Cagnoni Carlos Cotta Francisco Fernández Vega Gianni A. Caro Rolf Drechsler Anikó Ekárt Anna I. Esparcia-Alcázar Muddassar Farooq William B. Langdon Juan J. Merelo-Guervós Mike Preuss Hendrik Richter Sara Silva Anabela Simões Giovanni Squillero Ernesto Tarantino Andrea G. B. Tettamanzi Julian Togelius Neil Urquhart A. Şima Uyar Georgios N. Yannakakis

ISBN: (数字)9783642291784

ISBN: (纸本)9783642291777

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 54 revised full papers presented were carefully reviewed and selected from 90 submissions. EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

关键词： Computation by Abstract Devices Programming Techniques computer Communication Networks Math Applications in computer science Image Processing and computer vision Artificial Intelligence

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